社论
Bridging the divide between qualitative and
quantitative science studies
Loet Leydesdorff1
, Ismael Ràfols2
, and Staša Milojevic(西德:1)3
1Amsterdam School of Communication Research (ASCoR), University of Amsterdam,
邮政信箱 15793, 1001 NG Amsterdam, 荷兰人
2Centre for Science and Technology Studies (CWTS), 莱顿大学, Leiden,
荷兰人 & SPRU (Science Policy Research Unit), University of Sussex, 英国
3Center for Complex Networks and Systems Research, The Luddy School of Informatics,
计算, and Engineering, 印第安纳大学, 布卢明顿, 美国
1.
介绍
In January 2019, the Editorial Board of the Journal of Informetrics decided to resign following a
series of disagreements with Elsevier. In collaboration with the International Society for
Scientometrics and Informetrics (ISSI) and MIT Press, the Editorial Board thereupon launched this
journal: Quantitative Science Studies (QSS). The launch of QSS offers an opportunity to rethink
the contents and research agenda of the journal, and marks a turn from the focus on “metrics” to
science studies. Such a shift, reflected also in the name change, indicates the intention to seek
closer connections with colleagues in “qualitative science and technology studies” and take more
distance from journals focusing on specialist “metrics” (Milojevic(西德:1)& 莱德斯多夫, 2013).
The goal of this special issue is to explore the relations among and promote conversations between
quantitative science studies and neighboring fields. 为此, we invited a number of colleagues
conducting research relevant to this theme to articulate the relations between their research and QSS,
and to formulate challenges and research agendas for synergies between qualitative and quantitative
approaches in the broad area of Science and Technology Studies (超导系统), science-policy analyses,
innovation studies, the sociology of science, the science of science, and related domains. 他们的
response generated 11 articles and one letter that provide a rich panorama of views and exciting ideas
for building bridges and pursuing research agendas that have the potential to advance our knowledge
about science, scientific knowledge production, and the scientific workforce, as well as to promote
the responsible and sustainable usage of metrics for evaluation and policy.
2. THE “DIVIDE BETWEEN QUALITATIVE AND QUANTITATIVE” IN SCIENCE STUDIES
The idea of a main “divide” between qualitative and quantitative STS originated in relatively recent
studies that examined the relationship between qualitative and quantitative STS empirically.
Leydesdorff and Van den Besselaar (1997) argued on the basis of aggregated citation relations
among journals that three main groups of journals can be distinguished: one more specifically
qualitative oriented (例如, Social Studies of Science), one specifically focusing on quantitative
science studies (例如, Scientometrics), and a third interfacing between quantitatively oriented
journals and innovations studies (例如, Research Policy). From the latter perspective, 然而,
马丁, Nightingale, and Yegros-Yegros (2012, p. 1194) stated that
STS today is a rather divided community, with quantitative scientometrics and qualitative STS
researchers operating largely in isolation from one another, one or two individual exceptions
notwithstanding. The qualitative side of STS continues to expand its work on technology
(including constructive technology assessment) and innovation, with the original programme
开放访问
杂志
引文: 莱德斯多夫, L。, Ràfols, 我。, &
Milojević, S. (2020). Bridging the divide
between qualitative and quantitative
science studies. Quantitative Science
学习, 1(3), 918–926. https://doi.org/
10.1162/qss_e_00061
DOI:
https://doi.org/10.1162/qss_e_00061
通讯作者:
Loet Leydesdorff
loet@leydesdorff.net
Handling Editors:
Loet Leydesdorff, Ismael Rafols,
and Staša Milojević
版权: © 2020 Loet Leydesdorff,
Ismael Ràfols, and Staša Milojević.
在知识共享下发布
归因 4.0 国际的 (抄送 4.0)
执照.
麻省理工学院出版社
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Bridging the divide between qualitative and quantitative science studies
of work analysing the social influences on the content of science having diffused into the
mainstream and now attracting less interest. 同时, scientometric research has
been moving beyond science into areas previously the domain of traditional sociology (这样的
as innovation and the analysis of social networks within and between organisations), 还有
as forming links with information science (as reflected, 例如, in the recent creation of
the Journal of Informetrics).
On the basis of studying 136 chapters in both quantitative and qualitative handbooks of
科学技术研究, Milojevic(西德:1), Sugimoto, 等人. (2014) concluded that “a great
divide” has structured STS intellectually. 然而, these authors added that
[哦]ne of the interesting findings of this study is the identification of chapters of shared
interest across the qualitative and quantitative divide and the nuanced differences when
it comes to studying the topics covered in these chapters: 技术, gender and policy.
The discussion about a divide between qualitative and quantitative STS is by no means new to
the field. In December 1987, 例如, a workshop was organized by John Irvine, Anthony van
Raan, and one of us (莱德斯多夫 ) on “the relations between qualitative theory and scientometric
methods in science and technology studies.” This resulted in a special issue of Scientometrics in
1989 containing more than 300 页面 (卷. 15, issues 5–6, PP. 333–631).
At the workshop, John Irvine and Ben Martin (1989) contributed a paper entitled “International
comparisons of scientific performance revisited,” which offered new perspectives on the measure-
ment of national research performance. Michel Callon and his coauthors (Françoise Bastide and
Jean-Pierre Courtial) presented the co-word model (Bastide, Courtial, & Callon, 1989), 和
Anthony van Raan presented a paper (coauthored with Harry Peters) entitled “Dynamics of a
scientific field analysed by co-subfield structures” (van Raan & Peters, 1989) These three programs
是, 除其他外, elaborated in the decades since. In the introduction to the special issue,
莱德斯多夫, 尔湾, and Van Raan (1989, p. 333) formulated as follows:
There is growing recognition of the need to integrate qualitative theorizing in the philoso-
物理层, sociology and history of science with the quantitative perspectives provided by scien-
tometric studies. 一方面, the use of scientometric indicators in policy analysis has
stimulated debates on what exactly various indicators employed indicate, given the signif-
icant conceptual and technical problems that exist in measurement. 另一方面, 这
increased availability of large data-bases challenges researchers in the field of science and
技术研究 (S & TS) to test more rigorously their hypotheses concerning the various
aspects of scientific and institutional developments.
In a recent handbook of qualitative STS, Wyatt, Milojevic(西德:1), 等人. (2017, p. 87) formulated
the following evaluation of research efforts bridging the divide:
Scientometrics and qualitative approaches within STS share a common origin, 即使
they have grown apart over the past decades in terms of research practices, 规范
and standards. Different skills are needed, and the epistemological assumptions are also
不同的. 然而, both quantitative and qualitative STS have always shared a deep
commitment to the empirical study of science and technology, and practitioners of both
can be reflexive about their own knowledge production practices.
总共, although there is empirical evidence for a divide between qualitative and quanti-
tative STS, one can also find efforts to bridge this gap over the past decades.
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Bridging the divide between qualitative and quantitative science studies
3. THE INTELLECTUAL ORIGINS OF THE DIVIDE
Notwithstanding these common interests in bridging the divide, the tensions between qualitative
and quantitative science studies have been constitutive of the field. In a review article entitled
“Quantitative measures of communication in science: A critical overview,” David Edge (1979,
p. 114)—at the time the editor of Social Studies of Science—for example, criticized quantitative
science studies in the following strong wording:
One is tempted to say that formal communication in science is “the tip of the iceberg,” were
it not for two facts: (A) the “tip” is very large, extensive and important; 和 (乙) there is every
indication that the “tip” is radically different in kind from what is “below the waterline.”
(Perhaps “the soft underbelly of science” might be a more appropriate metaphor!)
Edge’s programmatic perspective of “following the actors” was committed to the “strong
program” in the sociology of scientific knowledge (Bloor, 1976). In this sociology of scientific
知识, it is claimed that the content of science can be explained in terms of sociocognitive
兴趣. 从这个角度来看, the sciences can be considered as belief structures attributed to
社区. The evidence supporting the claim of truth in science is constructed (Fuller, 2018).
These constructs can be deconstructed. 然而, an analyst cannot then escape from the
reflexive conclusion that one’s own knowledge claim is also constructed; all debates and
arguments thus tend to become matters of interests and opinion (例如, Woolgar, 1988).
Unlike an anthropological focus on practices, the study of science as a publication structure
allows for a more distanced approach. The dynamics of the literature are sometimes very different
from that of science as a social process. It seems to us that this “double hermeneutics” in terms
of formal and nonformal communications is unavoidable in science studies (Giddens, 1976)
because of the dynamics of the literature enabling us to move back and forth between contexts
of discovery and justification (例如, 迈尔斯, 1985). The textual layer (the library, the archive, ETC。) 是
structured with reference to disciplines that also operate as selection mechanisms. The practices
generate variation and novelty, that is reflected in the texts (Callon, Law, & 瑞普, 1986; Callon,
Courtial, 等人。, 1983), and the discursive layer has a dynamic of its own (吉尔伯特, 1977;
Mulkay, Potter, & Yearley, 1983).
The context of application in research evaluations, technology assessments, and science and tech-
科学 (S&时间) policy analyses has added a third “mode of knowledge production” to the field of STS
during the last decades (Gibbons, Limoges, 等人。, 1994). Both qualitative and quantitative science
studies have been challenged by priority programs such as the National Science Foundation’s
“Science of Science and Innovation Policies,” now replaced by the program “Science of Science:
发现, 沟通, and Impact” (比照. Husband Fealing, Lane, Marburger III, & Shipp,
2011; Marburger III, 2005). The European Framework and Horizons Programs call on STS from
the perspective of applications. Perhaps the pressure of funding agencies on this field has in the mean-
time become a unifying factor, because one often needs a variety of perspectives in studies with
normative objectives and implications. 然而, these are empirical questions.
While the differing contexts can be distinguished analytically, they are interacting in the prac-
tices which are under study when “following the actors.” Pickering (1995), 例如, proposed
the metaphor of a “mangle of practice.” In the so-called “sociology of translations,” heterogeneous
网络 (representing people, 文本, cognitions, 资金, and subjects of study (例如, scallops
[Callon, 1986]) are analyzed in terms of translations from one co-word map into another
(Callon et al., 1983). Such heterogeneity—including, 例如, also “nonhumans”— provides
resources for revisions and for changes.
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Bridging the divide between qualitative and quantitative science studies
It seems to us that this focus on “heterogeneity” at both the substantive and methodological
levels is not so different from Merton’s (1948) call for middle-range theories and pluriformity.
At the time, Merton (1948) made two points that are still relevant to the issue, as follows:
1. “[……] as a matter of plain fact the theorist is not inevitably the lamp lighting the way to
new observations. The sequence is often reversed. Nor is it enough to say that research
and theory must be married if sociology is to bear legitimate fruit. They must not only
exchange solemn vows—they must know how to carry on from there. Their reciprocal
roles must be clearly defined.” (p. 515)
“What we have said does not mean that the piling up of statistics of itself advances
理论; it does mean that theoretic interest tends to shift to those areas in which there
is an abundance of pertinent statistical data.” (PP. 512f.)
2.
We intend this issue as a contribution to the clarification and definition of the reciprocal roles of
quantitative and qualitative STS by focusing on research at the edge between the two approaches.
4. THE ORGANIZATION OF THE ISSUE
The contributions to this special issue have been grouped into four themes with three papers
each: (A) describing and questioning the divide between quantitative and qualitative science
学习, (乙) the use of numbers in decision-making addressing the usage of quantitative results
in the context of policy-making and research evaluations, (C) perspective and bridges show-
casing three currently very active research topics that attract researchers and scholars from a
wide range of science studies fields, 和 (d) future research programs laying out roadmaps for
the types of questions and approaches that can move the field forward.
4.1. Describing and Questioning the Divide
The three contributions in the first section of this collection address the divide from social, textual,
and epistemic perspectives, 分别. 第一的, Geoff Bowker contributes a letter entitled “Numbers
or no numbers in science studies.” The author narrates his experiences with the chasm that opened
between “quals” (“‘ethnomonsters”) and “quants” (“quantheads”) as political battles over hiring
decisions erupted between the two camps of a sociology department. During such episodes, 这
arguments of each side can be ignored by the other on the basis of legitimations other than scholarly
那些. Bowker (2020) argues for the importance of recognizing the complementary strengths of dif-
ferent approaches and for avoiding falling into dogmatic controversies.
The divide between qualitative and quantitative STS is empirically studied in a paper by Douglas
Kang and James Evans entitled “Against method: Exploding the boundary between qualitative and
quantitative studies of science.” The authors compare publications in qualitative and quantitative
sciences studies journals. The semantic analysis by Kang and Evans (2020) shows that qualitative
and quantitative analyses build on opposite normative worlds: Whereas qualitative studies dwell
on concepts such as “social,” “theory,” “political,” and “context,” quantitative analyses focus on
“performance,” “measure,” and “results.” The authors argue that these literatures have disparate
兴趣 (both cognitively and politically) and are written for different audiences. They envisage
that the further development of computer technologies will ease the tensions.
Whereas the two previous papers described a divide in qualitative and quantitative terms,
分别, Harriet Zuckerman closes this section with a paper entitled “Is ‘the time ripe’ for quan-
titative research on misconduct in science?,” in which she analyzes the “why” of the problems
involved in integrating the two perspectives. The argument runs as follows: If one relies on statistics
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Bridging the divide between qualitative and quantitative science studies
for making a qualitative argument, one risks making claims on the basis of data that can be decon-
structed from other perspectives. Official government statistics, 例如, are organized for an-
other objective. Using the case of misconduct in science, Zuckerman (2020) concludes that “a
healthy dose of skepticism is in order in evaluating both the findings of current quantitative studies
and of proposals for its remediation.”
4.2. Using Numbers in Decision-Making
As noted, a third context of applications has become constitutive of STS in terms of resources,
relations with clients, and legitimation (Gibbons et al., 1994). STS develops its own discourse
by analyzing among other things the discourses in the techno-sciences under study, 并由
“translating” both these discourses into political and managerial contexts, such as research
evaluations, technology assessments, and public debate. The three articles in the second section
explore the relationship between quantitative science studies and the use of numbers for decision-
making in these other contexts, including relations with industry and governments.
Quantification can be used and abused for justification in decision-making processes (Porter,
1996). The development of S&T indicators, 然而, has also led to controversies about their
使用. The feedback from policies and ideologies such as New Public Management have directly
influenced research agendas in scientometrics through consultancies and funding sources. 在他们的
纸, entitled “The impact of J. D. Bernal’s thoughts in the science of science upon China:
Implications for today’s quantitative studies of science,” Yong Zhao, Jian Du, and Yishan Wu
discuss the contribution of John Desmond Bernal (例如, Bernal, 1939) to the “science of science”
and the ideological role that quantitative studies of science has played first in the Soviet Union, 但
also to this day in China. While the use of indicators for policy purposes has been associated in the
West with New Public Management and neoliberal policies (巴罗斯, 2012; 力量, 2005), 这些
indicators and a systems perspective were embraced by communist regimes, which at the time
believed in the virtues of central planning. 赵, Du, and Wu (2020) plead for a reflection on these
alternative routes as a means to achieve a more harmonious integration between qualitative and
quantitative STS in other countries. 然而, there has been much debate in recent years over the
potentially problematic consequences of the use of S&T indicators (Barré, 2019; Weingart, 2005),
particularly in evaluation studies (de Rijcke et al., 2016; DORA, 2015; 希克斯, Wouters, 等人。, 2015).
The two following contributions on the policy use of S&T indicators reflect on the conditions
ofuse of indicators in the research system and emphasize the importance of appropriate under-
standings of theoretical framings and policy contexts for the successful use of S&T indicators. 在
their paper entitled “Powerful numbers: Exemplary quantitative studies of science that had policy
impact,” Diana Hicks and Kimberley Isett endorse the view that quantitative analysis may have a
positive impact on policies as an evidence base, but they note that the evidence “only rarely has a
notable policy impact.” Hicks and Isett (2020) further explore the conditions that enable “numbers”
to make a difference in decision-making. The study describes how the relevance, 合法性, 和
accessibility of the studies are important in the translation of scientific results to generate policy
impact—and how this “evidence” has both quantitative and qualitative components.
Thomas Heinze and Arlette Jappe use the sociology of professions to compare the contrasting
uses of bibliometrics in Dutch and Italian research evaluations.1 In this paper entitled
“Quantitative science studies should be framed with middle-range theories and concepts from
the social sciences,” Heinze and Jappe (2020) argue that differences in institutionalization can
explain the quality of the evaluations. In the Netherlands, 例如, research evaluation is
1 See also Jappe, Pithan, and Heinze (2018) on the difficulties of professionalization in evaluative scientometrics.
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controlled by professional experts, whereas Italy has a centralized model co-opted by academic
精英. The study is meant as an example of how quantitative science studies would benefit from
framing “their data and analyses with middle-range sociological theories and concepts in order to
advance our understanding of institutional configurations of national research systems.”
4.3. Perspectives and Bridges
In the next section, we turn to research topics in science studies that have been addressed from
more than a single perspective and thus offer opportunities for cross-fertilizations among dis-
courses. As Kang and Evans have shown, some topics are best addressed either by qualitative ap-
proaches (例如, more related to practices) or by quantitative approaches (例如, more related to
表现). As noted, Milojevic(西德:1) 等人. (2014) flagged programs and studies that were remarkably
competent in crossing the divide for substantive and intellectual reasons. Data infrastructure,
性别, and geography are analyzed here as examples of possible bridging functions between
disciplinary traditions.
The contribution by Christine Borgman entitled “Whose text, whose mining, and to whose
benefit?” reminds us that the possibility of conducting quantitative science studies depends on data
availability. The availability of data is mediated by infrastructure and a political economy that
makes this possible. Borgman (2020) explains that while academic scholarship is becoming
increasingly open to reading, it has not become more open to mining. This is problematic because
“scholarly information retrieval has degraded, from customized discipline-specific tools to generic
search engines” and, 所以, data mining is necessary for searching information. The issue links
with “fake news” and “misconduct.” Borgman argues that research outcomes should be made
“open” to read and to mine—rather than having private companies controlling academic informa-
的. Current studies are often shaped by data availability, 哪个, 除其他事项外, tends to mar-
ginalize regions and disciplines with fewer economic resources (Vessuri, Guédon, & Cetto, 2014).
Mary Frank Fox’s review (entitled “Gender, 科学, and academic rank: Key issues and
approaches”) discusses gender inequalities in science and shows that scholarship in this topic
could benefit from different theoretical and methodological approaches. Fox aims to understand
the lower and slower promotion of women to full professor by focusing on (A) patterns of collab-
oration and (乙) evaluative practices. 狐狸 (2020) draws on empirical insights from surveys (例如, 狐狸
& Mohapatra, 2007), interviews (例如, Gaughan & Bozeman, 2016), and publication analysis (例如,
Macaluso, Larivière, 等人。, 2016), triangulating evidence in ways that make for robust scholarship.
Koen Frenken’s article entitled “Geography of scientific knowledge: A proximity approach”
shows how a topic such as “the process of rendering knowledge claims scientific” can draw on
and be enriched by combining insights from diverse disciplinary traditions. From economic geog-
拉菲, Frenken adopts the notion of proximity (Boschma, 2005), and situates his approach by
building on the insights of STS and the sociology of scientific knowledge (Shapin, 1995). 这
author proposes a theoretical framework and various empirical avenues (open to both qualitative
and quantitative inquiry) to study the diffusion of knowledge claims and the analysis of scientists’
mobility. Frenken’s focus enables him to move back and forth between diverse traditions without
the readers even noticing this. Frenken (2020) thus provides a focus on the topic that successfully
creates bridges beyond the conventional silos.
4.4. Future Directions
The three papers in the last section of this issue make programmatic proposals. These papers,
as well as Kang & 埃文斯 (多于), propose agendas that seek to overcome the methodological
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Bridging the divide between qualitative and quantitative science studies
dilemma of a choice between thick and situated versus thin and decontextualized approaches.
As Alberto Cambrosio, Jean-Philippe Cointet, and Alexandre Hannud Abdo explain in their
paper entitled “Beyond networks: Aligning qualitative and computational science studies”:
while thick descriptions of selected sites missed the configurational dimensions of the
collectives, resort to a few quantitative indicators to account for configurational complexity
destroyed for all practical purposes the very phenomena under investigation.
According to these authors, the research agendas point in different directions. The differences
suggest that methodological divergence is related to epistemological positions.
Cambrosio, Cointet, and Abdo’s interests lie in aligning quantitative empirical approaches with
the theorical frameworks of science studies. They argue that methods such as Actor-Network
Theory allow for cross-fertilizations between qualitative and quantitative approaches in STS.
They vindicate the tradition of science mapping using co-words (Callon et al., 1983, 1986) 和
its emphasis on heterogeneous networks, as against the mainstream citation-based and “clean”
(IE。, mono-thematic) ontologies dominant in scientometrics. The authors envisage how advanced
network analysis tools and natural language processing allow for an engagement with sociological
theories in STS, such as translation theory.
The second article in this section is Henry Small’s paper, entitled “Past as prologue:
Approaches to the study of confirmation in science.” Small (2020) is interested in methods
for the confirmation of knowledge claims in the face of an “anti-science bias” in the sociology
of science. He shares a personal and rich recollection of the collision between Mertonian and
constructivist science studies during the 1970s and 1980s. The use of Bayesian statistics pro-
vides insights into the nature of support across a large part of the literature of knowledge
索赔. While Small’s interest is about the “confirmation/disconfirmation” of facts, the method
he proposes can also be used for mapping whether and how certain organizations or funding
agencies support specific knowledge claims (Oreskes & 康威, 2011).
In their paper entitled “From indicators to indicating interdisciplinarity: A participatory
mapping methodology for research communities in-the-making,” Noortje Marres and Sarah
de Rijcke are interested in situating the insights of quantitative studies. Their point of departure
is the search for indicators of interdisciplinarity in artificial intelligence (人工智能). Given the multiple
interpretations of the notion of interdisciplinarity and the diverse understandings of AI, 他们
propose to shift from indicators to indicating. In the journey to indicating, science mapping
appears as a useful interface, allowing analysts and engaged stakeholders to align their methods
with their interpretations of interdisciplinarity and AI. Marres and de Rijcke (2020) authors
contribute to recent debates on the need to contextualize quantitative approaches with the
participation of relevant stakeholders, which is particularly relevant in decision-making (Barré,
2010; Ràfols, 2019).
总共, this collection of articles offers a panoramic view of the variety of current perspec-
tives on how quantitative science studies are related to qualitative science studies and neigh-
boring fields. Scholarly communication is specialist communication that needs to be
translated carefully when used in different contexts. It seems to us that both qualitative and
quantitative perspectives are needed in high-quality STS. To paraphrase the above quotation
from Merton (1948), the relations between qualitative and quantitative STS “should not only
remain solemn vows—one should know how to carry on from there.” These reciprocal roles
can then be elaborated in research designs and programs. The edge between qualitative and
quantitative approaches in STS has also been a source for our longer-term research programs.
Quantitative Science Studies
924
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Bridging the divide between qualitative and quantitative science studies
致谢
We are grateful to the authors of the papers for their collaboration and to Sally Wyatt for her
participation in the initiative for this theme issue. Cassidy Sugimoto supported the project as
the President of ISSI. We are grateful to the Technische Informationsbibliothek (TIB) – Leibniz
Information Centre for Science and Technology for covering the APCs of the papers published
in this special issue.
COMPETING INTERESTS
The authors have no competing interests.
资金信息
No funding was received for this research.
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